Volume-1 Issue-1, March 2011 – International Journal of Soft Computing and Engineering (IJSCE)

A015021111

IJSCE Journal — Wed, 29 Sep 2021 07:18:16 +0000

The International Journal of Soft Computing and Engineering (IJSCE) has ISSN: 2231-2307 (online), an open-access, peer-reviewed, periodical bi-monthly international journal. This journal is published by Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) in January, March, May, July, September and November.The journal aims to publish high-quality peer–reviewed original articles in the area of Soft Computing and Engineering that covers Data Communication and Networking, Artificial Intelligence and Neural Networking, Image Processing and Recognition, Software Engineering and Project Management (SEPM), Computer Graphics and Multimedia (CGM), Data Mining, Cryptography and Network Security, Smart Computing and Information Processing, Internet of Things (IoT), Computation Intelligence and Analytics, Machine Learning (ML) and Knowledge Mining (KM), Operating System, Data Base Management System (DBMS), Data Structure and Algorithm (DSA), Object Oriented Analysis and Design (OOAD), and all interdisciplinary streams of Soft Computing and Engineering. #Addressing, Routing, Switching and Location Management #Broadband, Mobile, Wired, Wireless Internet #Networks: Adhoc and Sensor Networks, High Speed Networks, Mobile and #Wireless Networks #Network Architectures #Network Based Applications #Network Protocols #Network Operations & Management #Network Security Trust & Privacy #Cross Layer Design and Optimization #Internet and Web Applications #Network Measurement & Performance Analysis #Next Generation Internet & Web Architectures #Peer to Peer and Overlay Networks #QOS And Resource Management #Recent Trends & Developments in Computer Networks #Self-Organizing Networks and Networked Systems #Ubiquitous Networks #Virtual & Overlay Networks #Wireless Mesh Networks and Protocols #Wireless Multimedia Systems #Personal and Wearable Networks #Information-Centric Networking #Embedded Networks #Opportunistic Networking #Delay-Tolerant Networks #Cognitive Radio Networks #Vehicular Networks #Smart Grid Communications #Underwater Sensor Networks #Cyber-Physical Systems #Social Networks #Green Networking #Overlay and Peer-To-Peer Networks #Local-Area and Metropolitan-Area Networks #Storage-Area Networks #Routing and Transport Protocols #Big Data Networking #Cloud Computing and Networking #Software Defined Networking and Network Function Virtualization #Internet of Things #Link Technologies #Adaptive Networking Applications #Authentication, Authorization, Accounting #Security and Privacy #Cross-Layer Optimization #Multimedia and Real-Time Communication #Machine-To-Machine Communications for Smart Environments #Smart Cities #Network Traffic Characterization and Measurements #Network Management, Reliability and QoS #Performance Evaluation of Networks #Testbeds for Network Experiments #Network Coding #Optical and High-Speed Access Networks #High Performance Computing #Digital System and Logic Design #Networked-Driven Multicourse Chips #Information-Centric Networking #Opportunistic Networking #Mobile and Ubiquitous Networking #Big Data Networking #Cloud Computing and Networking #Software Defined Networking and Network Function Virtualization #Adaptive Networking Applications #Antenna and Communications Devices #Microstrip Antenna #Microwave #Radar and Satellite #Smart Antenna #MIMO Antenna #Wireless Communication #RFID Network and Applications #5G Communication #6G Communication #Neural Networks #Fuzzy Logic #Simulated Biological Evolution Algorithms (Like Genetic Algorithm) #Ant Colony Optimization(etc) #Reasoning and Evolution #Intelligence Applications #Computer Vision and Speech Understanding #Multimedia and Cognitive Informatics #Data Mining and Machine Learning Tools #Heuristic and Ai Planning Strategies and Tools #Computational Theories of Learning #Technology and Computing (Like Particle Swarm Optimization) #Intelligent System Architectures #Knowledge Representation #Bioinformatics #Natural Language Processing #Multiagent Systems #Supervised Learning #Unsupervised Learning #Deep Learning #Big Data and Ai Approaches #Reinforcement Learning #And Learning with Generative Adversarial Networks #Regression and Prediction #Problem Solving and Planning #Clustering #Classification #Neural Information Processing #Vision and Speech Perception #Heterogeneous and Streaming Data #Probabilistic Models and Methods #Reasoning and Inference #Marketing and Social Sciences #Knowledge Discovery #Web Mining #Information Retrieval #Design and Diagnosis #Game Playing #Streaming Data #Music Modelling and Analysis #Robotics and Control #Multi-Agent Systems #Active Vision and Robotic Systems #Architecture of Imaging and Vision Systems #Autonomous Vehicles #Character and Handwritten Text Recognition #Chemical and Spectral Sensitization #Chemistry of Photosensitive Materials #Coating Technologies #Coding and Transmission #Cognitive Aspects of Image Understanding #Color Imaging #Communication of Visual Data #Data Fusion from Multiple Sensor Inputs #Display and Printing #Document Image Understanding # Generation and Display #Holography #Image Analysis and Interpretation #Image Capturing #Image Databases #Image Generation #Image Manipulation #Image Permanence #Image Processing #Image Processing Applications #Image Processing: Coding Analysis and Recognition #Image Representation #Image Sensing #Imaging Systems and Image Scanning #Implementation and Architectures #Latent Image #Materials for Electro-Photography #Monitoring and Surveillance #Network Architecture for Real-Time Video Transport #New Visual Services Over ATM/Packet Network #Non-Impact Printing Technologies #Object Modeling and Knowledge Acquisition #Photoconductors #Photographic Emulsions #Photopolymers #Prepress and Printing Technologies #Processing and Analysis #Protocols for Packet Video #Remote Image Sensing #Retrieval and Multimedia #Scene Modeling #Signal-Processing Aspects of Image Processing #Storage and Transmission #Video Coding Algorithms and Technologies for ATM/P #Ethics of Software Engineering and Management #Software Life Cycles Development Models #Project Planning and Management #Software Requirements Analysis #Software Design Analysis #Software Testing and Integration #Software Implementation and Maintenance #Software Maintenance and Maintainability #Software Metrics or Attributes #Software Risk Assessment and Containment #Reliability #Software Quality and Quality Assurance #Software Cost Estimation #Object Oriented Developments #Object Oriented Metrics #Object Oriented Testing #Formal Notations #3D Reconstruction #Computer Animation #Computational Fabrication #Computational Geometry #Computational Photography #Computer Vision for Computer Graphics #Data Compression for Graphics #Geometric Modelling #Geometric Processing #HCI and Computer Graphics #Human Modelling #Image Analysis #Image Based Rendering #Image Processing #Machine Learning for Graphics #Medical Imaging #Pattern Recognition #Physically Based Modelling #Illumination and Rendering ethods #Robotics and Vision #Saliency Methods #Scientific Visualization #Shape and Surface Modelling #Shape Analysis and Image Retrieval #Shape Matching #Sketch-based Modelling #Solid Modelling #Stylized rendering #Textures #Virtual and Augmented Reality #Visual Analytics #Volume Rendering #Data Mining #Data Science #Big Data #Data Warehouse #Visualization #Security #Privacy #Big DaaS #Scalable Computing #Cloud Computing #Knowledge Discovery #Integration #Transformation #Information Retrieval #Social Data and Semantics #Mining Functions #Data Regression #Data Classification #Anomaly Detection #Data Clustering #Data Association #Data Regression #Data Cleaning #Feature Selection and Extraction #Data Mining Algorithms #Apriori #Decision Tree #Generalized Linear Models #K-Means #Minimum Description Length #Naive Bayes #Non-Negative Matrix Factorization #0-Cluster #Support Vector Machines #Data Preparation #Mining Unstructured Data #Artificial Intelligence #Future Directions and Challenges in Data Mining #Industrial Challenges in Data Mining #Cryptographic Protocols #Cryptography and Coding #Untrace-Ability #Privacy and Authentication #Key Management #Authentication #Trust Management #Quantum Cryptography #Computational Intelligence in Security #Artificial Immune Systems #Biological & Evolutionary Computation #Intelligent Agents and Systems #Reinforcement & Unsupervised Learning #Autonomy-Oriented Computing #Coevolutionary Algorithms #Fuzzy Systems #Biometric Security #Trust Models and Metrics #Regulation and Trust Mechanisms #Data Integrity #Models for Authentication #Trust and Authorization #Wireless Network Security #Information Hiding #Data & System Integrity #Access Control and Intrusion Detection #Intrusion Detection and Vulnerability Assessment #Authentication and Non-Repudiation #Identification and Authentication #Insider Threats and Countermeasures #Intrusion Detection & Prevention #Secure Cloud Computing #Security Information Systems Architecture and Design and Security Patterns #Security Management #Security Requirements (Threats, Vulnerabilities, Risk, Formal Methods, etc.) #Sensor and Mobile ad hoc Network Security #Service and Systems Design and QOS Network Security #System Security #Intrusion Detection #Secure end Systems #Secure Operating Systems #Data Base Security #Security Infrastructures #Security Evaluation #Software Security #Security and Privacy in Mobile Systems#Security and Privacy in Pervasive/Ubiquitous Computing #Security and Privacy in Web Services #Security and Privacy Policies #Security Area Control #Security Deployment #Security Engineering #Security for Grid Computing #Security in Distributed Systems #Network Security #Internet Security #Firewalls #Mobile Security #Security Agents #Protocols #Anti-Virus and Anti-Hacker Measures #Content Protection #Software Protection #Tamper Resistant Software #Electronic Commerce #Electronic Government #Health #Telecommunications #Mobility #Foundations #Privacy #Access Control #Authentication #Identification #Applied Cryptography #Formal Methods in Information Security #IoT & IoE & Edge Computing #Distributed Mobile Applications Utilizing IoT #Security, Privacy and Trust in IoT & IoE #Standards for IoT Applications #Ubiquitous Computing #Blockchain-enabled IoT Device and Data Security and Privacy #Application of WSN in IoT #Cloud Resources Utilization in IoT #Wireless Access Technologies for IoT #Mobile Applications and Services for IoT #Machine/ Deep Learning with IoT & IoE #Smart Sensors and Internet of Things for Smart City #Logic, Functional programming and Microcontrollers for IoT #Sensor Networks, Actuators for Internet of Things #Data Visualization using IoT #IoT Application and Communication Protocol #Big Data Analytics for Social Networking using IoT #IoT Applications for Smart Cities #Emulation and Simulation Methodologies for IoT #IoT Applied for Digital Contents #Soft Computing #Advance Ubiquitous Computing #Parallel Computing #Distributed Computing #Machine Learning #Information Retrieval #Expert Systems #Data Mining #Text Mining #Data Warehousing #Predictive Analysis #Data Management #Big Data Analytics #Big Data Security #Nature Inspired Computing #Reconfigurable Computing #Cloud, Cluster, Grid and P2P Computing #Biomedical Computing #Green Computing #Mobile Computing #Nano Ubiquitous Computing #Context Awareness and Personalization, Autonomic and Trusted Computing #Internet Computing #Sequential, Parallel and Distributed Algorithms and Data Structures #Approximation and Randomized Algorithms #Graph Algorithms And Graph Drawing #On-Line and Streaming Algorithms #Analysis of Algorithms and Computational Complexity #Algorithm Engineering #Web Algorithms #Exact And Parameterized Computation #Algorithmic Game Theory #Computational Biology #Foundations of Communication Networks #Computational Geometry #Discrete Optimization #Software Engineering Methodologies #Agent-based Software Engineering #Artificial Intelligence Approaches to Software Engineering #Component-based Software Engineering #Embedded and Ubiquitous Software Engineering #Aspect-based Software Engineering #Empirical Software Engineering #Search-Based Software Engineering #Automated Software Design and Synthesis #Computer-Supported Cooperative Work #Automated Software Specification #Reverse Engineering #Software Engineering Techniques and Production Perspectives #Requirements Engineering #Software Analysis, Design and Modelling #Software Maintenance and Evolution #Software Engineering Tools and Environments #Software Engineering Decision Support #Software Design Patterns #Software Product Lines #Process and Workflow Management #Reflection and Metadata Approaches #Program Understanding and System Maintenance #Software Domain Modelling and Analysis #Software Economics #Multimedia and Hypermedia Software Engineering #Software Engineering Case Study and Experience Reports #Enterprise Software, Middleware, and Tools #Artificial Intelligent Methods, Models, Techniques #Artificial Life and Societies #Swarm Intelligence #Smart Spaces #Autonomic Computing and Agent-Based Systems #Autonomic Computing #Adaptive Systems #Agent Architectures, Ontologies, Languages and Protocols #Multi-Agent Systems #Agent-Based Learning and Knowledge Discovery #Interface Agents #Agent-Based Auctions and Marketplaces #Secure Mobile and Multi-Agent Systems #Mobile agents #SOA and Service-Oriented Systems #Service-Centric Software Engineering #Service Oriented Requirements Engineering #Service Oriented Architectures #Middleware for Service Based Systems #Service Discovery and Composition #Service Level Agreements (Drafting, Negotiation, Monitoring and Management) #Runtime Service Management #Semantic web #Data Modelling, Mining and Data Analytics #Aggregation, Integration, and Transformation #Web and Text Mining #Data Mining Methods, Techniques, and Tools #Data Analytics Modelling and Algorithms #Patterns and Frameworks #Data Visualization #Knowledge Systems and Engineering #Knowledge Acquisition #Knowledge-based and Expert Systems #Knowledge Representation and Retrievals #Knowledge Engineering Tools and Techniques #Time and Knowledge Management Tools #Knowledge Modelling, Integration, Transformation, and Management #Uncertainty Knowledge Management #Knowledge Visualization #Mobile Computing and Mobile System Engineering #Mobile App Design and Development #Innovative Mobile Applications #Pervasive Computing #Mobile System Validation and Test Automation #Software & System Quality of Service #Soft Computing #Software and System Testing Methods #Quality Assurance Process, Standards, and Systems #Software Safety Systems #Software Test Automation and Tools #Software Dependability, Reliability, Scalability #Software & System Security #Software and System Security and Privacy #Mobile App Security and Privacy #Encryption Methods and Tools #Security Service Systems #Cloud, Sensor Cloud and Mobile Cloud Security #Mobile System Integrity, Security, And Fault Tolerance #Emergent Topics #Cloud Computing and Innovative Cloud-Based Application Systems #Mobile Cloud Computing and Application Services #Big Data Analytics Application Systems #Innovative Sensing Cloud and Systems #Large-Scale Cyber Systems #IoT and Smart City Application Systems #Big Data Quality Validation #Big Data Application Quality Services #Smart Learning and Innovative Education Systems #Learning Software Design Engineering #Smart Learning Methods and Environments #Online Learning Systems #Mobile Enabled Learning Systems and Tools #PhD Academic #Scopus #SCI #LatticeScience #Springer, #ScienceDirect #IEEE #Mendeley #Research #Scholarship #UGC #SSRN #ESCI #Science #Journal #Conference #SSRN #PubLons #PhD #Academic #Scopus #SCI #LatticeScience #Springer, #ScienceDirect #IEEE #Mendeley #Research #Scholarship #UGC #SSRN #LatticeScience #ESCI #Science #Journal #Conference #SSRN #PubLon

Efficient Coding Mechanism for Low Power Consumption in Wireless Programmable Devices
Kavita Deshmukh¹, Deepshikha Patel², Nitesh Gupta³, Shiv Kumar⁴
¹Kavita Deshmukh, Department of Information Technology, Technocrats Institute of Technology, Bhopal, (M.P.), India.
²Prof. Deepshikha Patel, Department of Information Technology, Technocrats Institute of Technology, Bhopal, (M.P.), India.
³Prof. Nitesh Gupta, Head of Department Information Technology, Technocrats Institute of Technology, Bhopal, (M.P.), India.
⁴Prof. ShivKumar, M.Tech. Coordinator, Department of Information Technology, Technocrats Institute of Technology, Bhopal, (M.P.), India.
Manuscript received on February 28, 2011. | Revised Manuscript received on March 02, 2011. | Manuscript published on March 05, 2011. | PP: 57-61 | Volume-1 Issue-1, March 2011. | Retrieval Number: A015021111
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Due to the continuous advancement in technology embedded devices are playing important role in everyone’s day to day life. Everyone is moving towards wireless embedded systems, but there is important concern about power consumption in such devices. While designing a lot of care has to be taken especially in power optimization because there is no regular power supply in this kind of devices. Power optimization can be done either by changes in hardware components or changes in software programs developed for various applications. Changes in hardware, is vendor dependent and only software level changes can be done after the manufacturing of the device. This paper represents software level methods for optimizing the power in ireless embedded devices. Previously loop optimization methods where used and tested to reduce the power consumption by some degree, similarly loop unrolling and loop alignment were also used in the application to improve the performance in terms of power. In this paper we are combining some software level methods like nested switches, no of parameters , no of local variables , size of constructor, data type etc. with the loop unrolling. Our coding methodology will improve the program for consumption of the power while executing various instructions under the embedded systems.
Keywords: Embedded systems, power optimization, software level methods, loop optimization, coding mechanism.

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A016021111

IJSCE Journal — Wed, 29 Sep 2021 06:56:33 +0000

A Novel Approach to Enhance Robustness in Steganography Using Multiple Watermark Embedding Algorithm
S. Praveen Kumar¹, K. Anusha², R.Venkata Ramana³
¹S.Praveen Kumar, Department of Information Technology, GITAM University, Visakhapatnam, Andhra Pradesh, India.
²K.Anusha, Department of Information Technology, GITAM University, Visakhapatnam, Andhra Pradesh, India.
³R.Venkata Ramana, Department of Information Technology, GITAM University, Visakhapatnam, Andhra Pradesh, India.
Manuscript received on February 28, 2011. | Revised Manuscript received on March 02, 2011. | Manuscript published on March 05, 2011. | PP: 50-56 | Volume-1 Issue-1, March 2011. | Retrieval Number: A016021111
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper deals with an enhanced technique that improves robustness in steganography. A multiple watermark embedding algorithm has been proposed to embed multiple text messages as watermarks simultaneously in the same watermark space while minimizing the watermark (distortion) energy. The watermark is embedded in the DCT coefficients of the green channel of the color image. The algorithm takes into account the perceptual capacity of each coefficient inside the DCT blocks before embedding the watermark information. Therefore, the first 16 low frequency coefficients (excluding the DC value) in the 8×8 DCT block was screened and the eight coefficients with the maximum magnitudes were selected for embedding. The algorithm used is blind and does not require the original image for extracting the watermark. The watermarking method is robust against JPEG compression, additive noise, cropping, scaling, low-pass and median filtering.
Keywords: Steganography, DCT, MWE, pseudo random bit sequence, pseudo random positive real numbers, zero –mean Gaussian with variance.

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A013021111

IJSCE Journal — Wed, 29 Sep 2021 06:49:28 +0000

Mobile SMS Classification an Application of Text Classification
Deepshikha Patel¹, Monika Bhatnagar²
¹Deepshikha Patel, Information Technology, Rajeev Gandhi Technical University, Bhopal, India.
²Monika Bhatnagar, Information Technology, Rajeev Gandhi Technical University, Bhopal, India.
Manuscript received on February 24, 2011. | Revised Manuscript received on March 02, 2011. | Manuscript published on March 05, 2011. | PP: 47-49 | Volume-1 Issue-1, March 2011. | Retrieval Number: A013021111
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Text Classification is the process of classifying documents into predefined classes based on its content. Text classification is important in many web applications like document indexing, document organization, spam filtering etc. In this paper we analyze the concept of a new classification model which will classify Mobile SMS into predefined classes such as jokes, shayri, festival etc. All sms are converted into text documents. After preprocessing vector space model is prepared and weight is assigned to each term. In the proposed model we have used entropy term weighting scheme and then PCA is used for reparameterization. Artificial Neural Network is used for classification.
Keywords: Text Classification, Short messaging service (sms), feature selection, Principal Component Analysis, Neural Network.

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A017031111

IJSCE Journal — Wed, 29 Sep 2021 06:33:36 +0000

Signature Based Approach For Image Retrieval Using Color Histogram And Wavelet Transform
Wasim Khan¹, Shiv Kumar², Neetesh Gupta³, Nilofar Khan⁴
¹Wasim Khan is M.Tech student of Technocrats Institute of Technology, Bhopal, India.
²Prof. Shiv Kumar is with Technocrats Institute of Technology, Bhopal, India.
³Prof. Neetesh Gupta is with Technocrats Institute of Technology, Bhopal, India.
⁴Prof. Nilofar Khan is with Astral Institute of Technology & Research, Indore, India.
Manuscript received on February 24, 2011. | Revised Manuscript received on March 02, 2011. | Manuscript published on March 05, 2011. | PP: 43-46 | Volume-1 Issue-1, March 2011. | Retrieval Number: A017031111
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In this article, a method is proposed for image mining based on analysis of color and texture properties of an image. Color and texture are the primitive image descriptors in content based image retrieval systems. We first resize all the database images to obtained similar space. For color based Image Retrieval, HSV color model is used to obtain color histogram of image and for texture extraction Haar wavelet transform is used. Then the proposed method evaluates different number of signatures for HSV and wavelet coefficients. Similar process is applied on the submitted query image. Finally Euclidian distance between query image and database images is calculated and the images having minimum distances are extracted from the database as results.
Keywords: Color histogram, Content-based image retrieval, Euclidian distance, Haar wavelet transform. HSV model.

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A010021111

IJSCE Journal — Wed, 29 Sep 2021 06:23:46 +0000

Cluster-Tree based Data Gathering in Wireless Sensor Network
Gurpreet Singh Chhabra¹, Dipesh Sharma²
¹Gurpreet Singh Chhabra, M.Tech Scholar (CSE) from RITEE Raipur (C.G.), India.
²Dipesh Sharma, Reader CSE Department, RITEE Raipur (C.G.), India.
Manuscript received on February 20, 2011. | Revised Manuscript received on February 27, 2011. | Manuscript published on March 05, 2011. | PP: 27-31 | Volume-1 Issue-1, March 2011. | Retrieval Number: A010021111
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: WSN consisting of a large number of small sensors with low-power transceivers can be an effective tool for gathering data in a variety of environments. As sensor nodes are deployed in sensing field, they can help people to monitor and aggregate data. Researchers also try to find more efficient ways of utilizing limited energy of sensor node in order to give longer life time of WSNs. Network lifetime, scalability, and load balancing are important requirements for many data gathering sensor network applications. Therefore, many protocols are introduced for better performance. In the available literature, multi-hop routing protocol is well known for power saving in data gathering [5]. Researchers have used such types of the cluster-based (e.g., LEACH, EERP), the chain-based (e.g. PEGASIS) and the tree-based (e.g. TREEPSI) to establish their energy-efficient routing protocols. In this paper, we propose an improved version which uses both cluster and tree based protocols. The proposed protocol improves the power consumption by improving FND.
Keywords: Wireless Sensor Networks (WSNs), First Node Death (FND), Energy efficient, Multi-hop routing protocol.

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A008021111

IJSCE Journal — Wed, 29 Sep 2021 06:18:34 +0000

Optimization of Association Rule Mining Apriori Algorithm Using ACO
Badri Patel¹, Vijay K Chaudhari², Rajneesh K Karan³, YK Rana⁴
¹Badri Patel, M.Tech., Department of IT, Technocrat Institute of Technology, Bhopal, (M.P.), India.
²Prof. Vijay K Chaudhari, Head, Department of Information Technology, Truba Institute of Technology, Bhopal, (M.P.), India.
³Prof. Rajneesh K Karan, Dean Academic, Radharaman Engineering College, Bhopal (M.P.), India.
⁴Prof. Y.K. Rana, Head, Department of Computer Science and Engineering & Informationa Technology, Radharaman Engineering College, Bhopal (M.P.), India.
Manuscript received on February 20, 2011. | Revised Manuscript received on February 27, 2011. | Manuscript published on March 05, 2011. | PP: 24-26 | Volume-1 Issue-1, March 2011. | Retrieval Number: A008021111
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Association rule mining is an important topic in data mining field. In a given large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. Apriori algorithm that generates all significant association rules between items in the database. On the basis of the association rule mining and Apriori algorithm, this paper proposes an improved algorithm based on the Ant Colony Optimization algorithm. We can optimize the result generated by Apriori algorithm using Ant colony optimization algorithm. The algorithm improved result produces by Apriori algorithm. Ant Colony Optimization (ACO) is a metaheuristic inspired by the foraging behavior of ant colonies. ACO was introduced by Dorigo and has evolved significantly in the last few years.
Keywords: Association rule mining, Apriori algorithm, Ant Colony Optimization (ACO) algorithm, data mining.

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A007021111

IJSCE Journal — Wed, 29 Sep 2021 06:12:23 +0000

Power Efficient Design of Counter on .12 Micron Technology
Simmy Hirkaney¹, Sandip Nemade², Vikash Gupta³
¹Simmy Hirkaney, Student of M.Tech. Final year, Technocrat Institute of Technology, Bhopal, (M.P.), India.
²Sandeep Nimade, Assistant Professor, Department of Electronics and Communication, Technocrat Institute of Technology, Bhopal, (M.P.), India.
³Vikash Gupta, Assistant Professor, Department of Electronics and Communication, Technocrat Institute of Technology, Bhopal, (M.P.), India.
Manuscript received on February 20, 2011. | Revised Manuscript received on February 27, 2011. | Manuscript published on March 05, 2011. | PP: 19-23 | Volume-1 Issue-1, March 2011. | Retrieval Number: A007021111
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: As chip manufacturing technology is suddenly on the threshold of major evaluation, which shrinks chip in size and performance is implemented in layout level which develops the low power consumption chip, using recent CMOS, micron layout tools. This paper compares 2 architectures in terms of the hardware implementation, power consumption and CMOS layout using Microwind CMOS layout tool. Thus it provides solution to a low power architecture implementation of Counter in CMOS VLSI. The Microwind program allows the designer to design and simulate an integrated circuit at physical description level.
Keywords: Microwind, micron Technology, layout, asynchronous counter.

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A005021111

IJSCE Journal — Wed, 29 Sep 2021 06:06:58 +0000

A Novel Approach to Intrusion Detection System using Rough Set Theory and Incremental SVM
Ghanshyam Prasad Dubey¹, Prof. Neetesh Gupta², Rakesh K Bhujade³
¹Ghanshyam Prasad Dubey is M.Tech Scholar in Department of Information Technology, Technocrats Institute of Technology, Bhopal. India.
²Prof. Neetesh Gupta is working as Head, Department of Information Technology, Technocrats Institute of Technology, Bhopal, India.
³Rakesh K Bhujade is working as Associate Professor Technocrats Institute of Technology, Bhopal, India.
Manuscript received on February 20, 2011. | Revised Manuscript received on February 27, 2011. | Manuscript published on March 05, 2011. | PP: 14-18 | Volume-1 Issue-1, March 2011. | Retrieval Number: A005021111
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Intrusion Detection System (IDS) is software and/or hardware designed to detect unwanted attempts at accessing, manipulating, and/or disabling of computer systems, mainly through a network, such as the Internet. These attempts may take the form of attacks, as examples, by crackers, malware and/or disgruntled employees. An IDS cannot directly detect attacks within properly encrypted trafficOn detection of such sign triggers of IDS to report them generate the alerts. These alerts are presented to a human analyst who evaluates them and initiates an adequate response. In Practice, IDSs have been observed to trigger thousands of alerts per day, most of which are mistakenly triggered by begin events such as false positive. This makes it extremely difficult for the analyst to correctly identify alerts related to attack such as a true positive. Recently data mining methods have gained importance in addressing network security issues, including network intrusion detection. Intrusion detection systems aim to identify attacks with a high detection rate and a low false positive. We use RST (Rough Set Theory) and Incremental SVM (Support Vector Machine) to detect intrusions. First, RST is used to preprocess the data and reduce the dimensions. Next, the features were selected by RST will be sent to SVM model to learn and test respectively. The method is effective to decrease the space density of data. Using this method, it can overcome the shortages of SVM time-consuming of training and massive dataset storage. The simulation experiments with KDD Cup 1999 data demonstrate that our proposed method achieves the increasing performance for intrusion detection.
Keywords: Intrusion Detection, Support Vector Machine, Rough Set Theory, Data Mining.

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A004021111

IJSCE Journal — Wed, 29 Sep 2021 06:01:28 +0000

Challenges for Mobile Wireless Devices for Next Generation in Pervasive Computing
Sanjay Sharma¹, Pushpinder Singh Patheja², Akhilesh A. Waoo³
¹Dr. Sanjay Sharma is Associate Professor in the department of computer application in MANIT, Bhopal, India.
²Pushpinder Singh Patheja is Research Fellow in the department of computer application in MANIT, Bhopal, India.
³T. Akhilesh A. Waoo is Research Fellow in the department of computer application in MANIT, Bhopal, India
Manuscript received on February 20, 2011. | Revised Manuscript received on February 27, 2011. | Manuscript published on March 05, 2011. | PP: 6-13 | Volume-1 Issue-1, March 2011. | Retrieval Number: A004021111
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Network computing and mobile computing are fast becoming a part of everyday life. We expect devices like PDAs, mobile phones, offices PCs and even home entertainment systems to access information and work together in one integrated system and the challenge is to combine these technologies into a seamless whole and on the Internet. The aim of Pervasive Computing is for computing available wherever it’s needed. It spreads intelligence and connectivity to more or less everything. So conceptually, ships, aircrafts, cars, bridges, tunnels, machines, refrigerators, door handles, lighting fixtures, shoes, hats, packaging clothing, tools, appliances, homes and even things like our coffee mugs and even the human body and will embedded with chips to connect to an infinite network of other devices and to create an environment where the connectivity of devices is embedded in such a way that it is unobtrusive and always available. Pervasive computing, therefore, refers to the emerging trend toward numerous, easily accessible computing devices connected to an increasingly ubiquitous network infrastructure.
Keywords: AMPS, CDMA, GSM, IMT-2000, Pervasive Computing, Ubiquitous Networks.

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A001021111

IJSCE Journal — Wed, 29 Sep 2021 05:40:49 +0000

Handwritten Multiscript Numeral Recognition using Artificial Neural Networks
Stuti Asthana¹, Farha Haneef², Rakesh K Bhujade³
¹Stuti Asthana is M.Tech Scholar from RKDF Institute of Science and Technology, Bhopal, India.
²Farha Haneef is M.Tech Coordinator in RKDF Institute of Science and Technology, Bhopal, India.
³Rakesh K Bhujade is with Technocrats Institute of Technology, Bhopal , India.
Manuscript received on February 20, 2011. | Revised Manuscript received on February 27, 2011. | Manuscript published on March 05, 2011. | PP: 1-5 | Volume-1 Issue-1, March 2011. | Retrieval Number: A001021111
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Handwritten Numeral recognition plays a vital role in postal automation services especially in countries like India where multiple languages and scripts are used .Because of intermixing of these languages; it is very difficult to understand the script in which the pin code is written. Objective of this paper is to resolve this problem through Multilayer feed-forward back-propagation algorithm using two hidden layer. This work has been tested on five different popular Indian scripts namely Devnagri, English, Urdu, Tamil and Telugu. Network was trained to learn its behavior by adjusting the connection strengths on every iteration. The resultant of each presented training pattern was calculated to identify the minima on the error surface for each training pattern. Experiments were performed on samples by using two hidden layers and the results revealed that as the number of hidden layers is increased, more accuracy is achieved in large number of epochs.
Keywords: Numeral Recognition, Artificial Neural Network, Supervised learning, Back Propagation Algorithm.

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